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        <h1 align="center">Optical Precision</h1>
		<p align="left">Of all of the factors impacting the efficacy of LRE, 
		optical precision is one of the most predominant. This is because the core functionality of LRE is based on analysis of 
		cycle efficiency (E<sub>C</sub>), which is calculated by dividing the 
		cycle fluorescence (F<sub>C</sub>) by the fluorescence reading produced by the 
		preceding cycle (F<sub>C-1</sub>):</p>
		<p align="center">
		<img border="0" src="images/ec_equation2.gif" width="187" height="58"></p>
		<p align="left">Due to this ratio-based determination, the accuracy of 
		E<sub>C </sub>determination is highly dependent on the precision of the fluorescence 
		readings, which is generally referred to as
		<a href="../glossary/glossary.html#Read_Precision">read precision</a>. </p>
		<p align="left">Maximizing the fluorescence intensity of an assay can 
		increase read precision. For example, white plates or tubes can increase 
		the fluorescence intensity 3-5X over that achieved with clear plates or 
		tubes. In 
		addition to increasing read precision, white plates or tubes also allow reaction 
		volume to be reduced (e.g. 10 <font face="Times New Roman">µ</font>l for 
		a 96 well plate). 
		The type of closure has also been found to impact read precision, with 
		seals being generally superior to caps, although this may not be true 
		in all cases. </p>
		<p align="left">By far the most prominent factor is the precision of the 
		instrument&#39;s optical system. For some instruments, such as the Agilent 
		Mx3000P, read precision can be increased by instructing the instrument 
		to take multiple readings (typically X3) for each cycle, which are 
		averaged by the Mx3000P software. Note however, that some instruments, such as the Applied Biosystems 7500, have been found to produce a high level of read precision 
		without any intervention. </p>
		<p align="left">Another method that has been found to dramatically increase read precision 
		for some instruments, is to conduct replicate reactions (typically 
		3-4 technical replicates), from which an 
		average profile is constructed. An average profile is generated by averaging, for each cycle, the 
		fluorescence readings from the resulting
		replicate profiles. Average profiles are automatically constructed by 
		the LRE Analyzer during data import. </p>
		<p align="left">It is also recommended that at least two replicates be 
		routinely conducted (three is even better), as this allows aberrant 
		profiles to be identified, based on how closely the profiles are 
		clustered. Note also, that low target quantity replicate profiles become 
		highly scattered as a result of Poisson distribution, as is described in 
		the <a href="../quantitative_accuracy/less_than_10molecules.html">&lt;10 
		Molecule Problem</a> page. </p>
		<div align="center">
			<p align="left">Differences in read precision, along with a general 
			assessment of its impact can be achieved by examining the 
			resulting LRE plots. The following examples where produced 
			by QuantiTect amplification of 100 fg of lambda gDNA and the CAL1 
			amplicon, using identical cycling regimes (95 <sup>o</sup>C-10 sec, 
			65 <sup>o</sup>C-120 sec ) and reaction volume (10
			<font face="Times New Roman">µ</font>l), which are in fact typical 
			calibration profiles used to conduct optical calibration. </p>
			<table border="1" width="537" height="326">
				<tr>
					<th height="17" width="527" colspan="2">Mx3000P vs. AB7500</th>
				</tr>
				<tr>
					<th height="17" width="261"><b>Replicate Profile</b></th>
					<th height="17" width="260"><b>Average Profile (X4 
					replicates)</b></th>
				</tr>
				<tr>
					<td height="60" width="261">
					<p align="center">Mx3000P<br>
					<img border="0" src="images/lre_plot_scattering1.gif" width="261" height="147"></td>
					<td height="60" width="260">
					<p align="center">Mx3000P<br>
					<img border="0" src="images/lre_plot_scattering2.gif" width="257" height="150"></td>
				</tr>
				<tr>
					<td height="143" width="261">
					<p align="center">AB7500<br>
					<img border="0" src="images/lre_plot_scattering3.gif" width="260" height="149"></td>
					<td height="143" width="260">
					<p align="center">AB7500<br>
					<img border="0" src="images/lre_plot_scattering4.gif" width="260" height="146"></td>
				</tr>
			</table>
		</div>
		<p align="left">This provides a nice example of how the 
		universal nature of lambda calibration profiles can be used for performance 
		benchmarking, which in addition to revealing differences in instrument 
		performance, can be used to examine performance differences between, 
		e.g., enzyme formulations and/or cycling regimes. </p>
		<p align="left">In this example, 
		it is evident that the read precision is increased, as reflected by a 
		reduction in the scattering within the Mx300P average profile, particularly for early cycles in which 
		reaction fluorescence is close to the limit of the instrument&#39;s 
		sensitivity. In contrast, the replicate 
		profile generated by the AB7500 has a similar read precision to that of the average 
		profile generated by the Mx3000P.</p>
		<p align="left">See also:<br>
		<a href="monitoring_assay_performance.html">Monitoring Assay Performance</a><br>
		<a href="../quantitative_accuracy/less_than_10molecules.html">The &lt;10 
		Molecule Problem</a><br>
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